def test_angle_offset():
"""
Tests if things are still correct when there is a 2PI offset in the angles.
"""
sino, angles = create_test_sino_2d()
parameters = get_test_parameter_set(2)
# reference
r1 = []
for p in parameters:
f1 = odtbrain.backpropagate_2d(sino, angles, weight_angles=False, **p)
r1.append(f1)
# with offset
angles[::2] += 2*np.pi*np.arange(angles[::2].shape[0])
r2 = []
for p in parameters:
f2 = odtbrain.backpropagate_2d(sino, angles, weight_angles=False, **p)
r2.append(f2)
# with offset and weights
r3 = []
for p in parameters:
f3 = odtbrain.backpropagate_2d(sino, angles, weight_angles=True, **p)
r3.append(f3)
assert np.allclose(np.array(r1).flatten().view(float),
np.array(r2).flatten().view(float))
assert np.allclose(np.array(r2).flatten().view(float),
np.array(r3).flatten().view(float))
def test_angle_swap():
"""
Test if everything still works, when angles are swapped.
"""
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_2d()
# remove elements so that we can see that weighting works
angles = angles[:-2]
sino = sino[:-2,:]
parameters = get_test_parameter_set(2)
# reference
r1 = []
for p in parameters:
f1 = odtbrain._Back_2D.backpropagate_2d(sino, angles, weight_angles=True, **p)
r1.append(f1)
# change order of angles
order = np.argsort(angles % .5)
angles = angles[order]
sino = sino[order,:]
r2 = []
for p in parameters:
f2 = odtbrain._Back_2D.backpropagate_2d(sino, angles, weight_angles=True, **p)
r2.append(f2)
assert np.allclose(np.array(r1).flatten().view(float),
np.array(r2).flatten().view(float))
def test_angle_offset():
"""
Tests if things are still correct when there is a 2PI offset in the angles.
"""
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_2d()
parameters = get_test_parameter_set(2)
# reference
r1 = []
for p in parameters:
f1 = odtbrain._Back_2D.backpropagate_2d(sino, angles, weight_angles=False, **p)
r1.append(f1)
# with offset
angles[::2] += 2*np.pi*np.arange(angles[::2].shape[0])
r2 = []
for p in parameters:
f2 = odtbrain._Back_2D.backpropagate_2d(sino, angles, weight_angles=False, **p)
r2.append(f2)
# with offset and weights
r3 = []
for p in parameters:
f3 = odtbrain._Back_2D.backpropagate_2d(sino, angles, weight_angles=True, **p)
r3.append(f3)
assert np.allclose(np.array(r1).flatten().view(float),
np.array(r2).flatten().view(float))
assert np.allclose(np.array(r2).flatten().view(float),
np.array(r3).flatten().view(float))
def test_2d_fmap():
myframe = sys._getframe()
sino, angles = create_test_sino_2d()
parameters = get_test_parameter_set(1)
r = []
for p in parameters:
f = odtbrain.fourier_map_2d(sino, angles, **p)
r.append(cutout(f))
if WRITE_RES:
write_results(myframe, r)
assert np.allclose(np.array(r).flatten().view(float), get_results(myframe))
def test_fmp_2d():
sino, angles = create_test_sino_2d(N=10)
p = get_test_parameter_set(1)[0]
# complex
jmc = mp.Value("i", 0)
jmm = mp.Value("i", 0)
odtbrain.fourier_map_2d(sino, angles, count=jmc, max_count=jmm, **p)
assert jmc.value == jmm.value
assert jmc.value != 0
def test_2d_backprop_full():
myframe = sys._getframe()
sino, angles = create_test_sino_2d(ampl_range=(0.9, 1.1))
parameters = get_test_parameter_set(2)
r = list()
for p in parameters:
f = odtbrain.backpropagate_2d(sino, angles, **p)
r.append(cutout(f))
if WRITE_RES:
write_results(myframe, r)
assert np.allclose(np.array(r).flatten().view(float), get_results(myframe))
def test_2d_backprop_full():
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_2d(ampl_range=(0.9,1.1))
parameters = get_test_parameter_set(2)
r = list()
for p in parameters:
f = odtbrain._Back_2D.backpropagate_2d(sino, angles, **p)
r.append(cutout(f))
if WRITE_RES:
write_results(myframe, r)
assert np.allclose(np.array(r).flatten().view(float), get_results(myframe))
def test_bpp_2d():
sino, angles = create_test_sino_2d(N=10)
p = get_test_parameter_set(1)[0]
# complex
jmc = mp.Value("i", 0)
jmm = mp.Value("i", 0)
odtbrain.backpropagate_2d(sino,
angles,
padval=0,
count=jmc,
max_count=jmm,
**p)
assert jmc.value == jmm.value
assert jmc.value != 0
def test_back2d():
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_2d(N=10)
p = get_test_parameter_set(1)[0]
# complex
jmc = mp.Value("i", 0)
jmm = mp.Value("i", 0)
f = odtbrain._Back_2D.backpropagate_2d(sino, angles, padval=0,
jmc=jmc,
jmm=jmm,
**p)
assert jmc.value == jmm.value
assert jmc.value != 0
def test_2d_backprop_real():
"""
Check if the real reconstruction matches the real part
of the complex reconstruction.
"""
sino, angles = create_test_sino_2d()
parameters = get_test_parameter_set(2)
# complex
r = list()
for p in parameters:
f = odtbrain.backpropagate_2d(sino, angles, padval=0, **p)
r.append(f)
# real
r2 = list()
for p in parameters:
f = odtbrain.backpropagate_2d(sino,
angles,
padval=0,
onlyreal=True,
**p)
r2.append(f)
assert np.allclose(np.array(r).real, np.array(r2))
def test_2d_backprop_real():
"""
Check if the real reconstruction matches the real part
of the complex reconstruction.
"""
myframe = sys._getframe()
myname = myframe.f_code.co_name
print("running ", myname)
sino, angles = create_test_sino_2d()
parameters = get_test_parameter_set(2)
# complex
r = list()
for p in parameters:
f = odtbrain._Back_2D.backpropagate_2d(sino, angles, padval=0,
**p)
r.append(f)
# real
r2 = list()
for p in parameters:
f = odtbrain._Back_2D.backpropagate_2d(sino, angles, padval=0,
onlyreal=True, **p)
r2.append(f)
assert np.allclose(np.array(r).real, np.array(r2))
def test_angle_swap():
"""
Test if everything still works, when angles are swapped.
"""
sino, angles = create_test_sino_2d()
# remove elements so that we can see that weighting works
angles = angles[:-2]
sino = sino[:-2, :]
parameters = get_test_parameter_set(2)
# reference
r1 = []
for p in parameters:
f1 = odtbrain.backpropagate_2d(sino, angles, weight_angles=True, **p)
r1.append(f1)
# change order of angles
order = np.argsort(angles % .5)
angles = angles[order]
sino = sino[order, :]
r2 = []
for p in parameters:
f2 = odtbrain.backpropagate_2d(sino, angles, weight_angles=True, **p)
r2.append(f2)
assert np.allclose(np.array(r1).flatten().view(float),
np.array(r2).flatten().view(float))
